code: def local_response_norm(
      x: torch.Tensor,
      size,
      /,
      *,
      bias: Optional[float] = 1.0,
      alpha: Optional[float] = 1.0,
      beta: Optional[float] = 0.5,
      average: bool = False,
      data_format: Optional[Literal["NHWC", "NCHW"]] = "NHWC",
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      if data_format == "NHWC":
          x = torch.permute(x, (0, 3, 1, 2))
      alpha = alpha * size if not average else alpha
      ret = torch.nn.functional.local_response_norm(
          x, size, alpha=alpha, beta=beta, k=bias
      )
      if data_format == "NHWC":
          ret = torch.permute(ret, (0, 2, 3, 1))
      return ret
  
file_path: ivy/ivy/functional/backends/torch/experimental/norms.py
imports: import torch
  from typing import Literal, Optional, Tuple
  from ivy.func_wrapper import with_supported_dtypes, with_unsupported_dtypes
  from ..None import backend_version
label_desc: Use image node_id 3 for calling a global function with example usage: local_response_norm() and returns: ret